AI-Driven Modernization: Overcoming Tech Debt for Card Issuers

Credit card issuers today stand at a crossroads. The rapid evolution of digital payments, rising customer expectations for hyper-personalized experiences, and an ever-tightening regulatory landscape are converging to create both unprecedented opportunities and daunting challenges. At the heart of these challenges lies a complex web of legacy technology, siloed data, and organizational inertia—collectively known as “tech debt.” For card issuers, overcoming these barriers is not just a matter of operational efficiency; it’s a strategic imperative for survival and growth. Artificial intelligence (AI) and machine learning (ML) are emerging as the catalysts capable of breaking through these barriers, enabling issuers to modernize, innovate, and lead in a digital-first world.

The Five Forms of Debt Hindering Card Issuers

Through extensive industry engagement, five critical forms of “debt” have been identified as the primary obstacles to digital transformation and AI adoption for card issuers:

Technology Debt: Outdated core systems and fragmented architectures slow innovation, increase risk, and make it difficult to integrate new AI-driven capabilities.
Data Debt: Poor data quality, siloed information, and lack of governance hinder the ability to leverage AI for personalization, risk management, and regulatory compliance.
Process Debt: Manual, paper-based, or inconsistent processes limit scalability, slow down onboarding, and increase operational costs.
Skills Debt: A shortage of AI and data talent impedes the ability to implement and scale new solutions, leaving issuers reliant on legacy ways of working.
Cultural Debt: Resistance to change and a lack of an “AI mindset” can stall transformation before it begins, preventing organizations from realizing the full value of modernization.

Addressing these debts holistically is essential for rapid, sustainable AI value creation. Leading card issuers are demonstrating that tackling these debts—by modernizing data infrastructure, building AI/ML catalogs, and driving new business models—lays the foundation for enterprise-scale AI adoption.

Why AI Is the Game Changer for Card Issuers

AI is not just another tool in the modernization toolkit—it is the catalyst capable of dismantling even the most persistent forms of tech debt. Over 80% of senior executives in financial services believe AI is the breakthrough needed to overcome entrenched technical debt. For card issuers, AI unlocks:

Hyper-personalization: Tailoring products, rewards, and communications to individual cardholder needs and behaviors, driving engagement and loyalty.
Real-time risk assessment: Leveraging diverse data sources to dynamically assess creditworthiness, detect fraud, and manage risk more effectively than traditional models.
Operational efficiency: Automating manual processes, from onboarding to compliance, reducing costs and accelerating speed to market.
Regulatory agility: Enabling proactive compliance monitoring and reporting, adapting quickly to evolving regulations and reducing the risk of costly penalties.

AI in Action: Modernizing Legacy Systems and Streamlining Compliance

AI-driven modernization is already delivering measurable impact across the card issuer value chain:

Legacy System Modernization: Generative AI and automation are accelerating the migration from mainframes and monolithic architectures to cloud-native, modular platforms. For example, Publicis Sapient’s collaboration with a major global bank leveraged generative AI to enhance the software development lifecycle, boosting efficiency by up to 40% and reducing modernization timelines from years to months.
Regulatory Compliance: AI-powered frameworks are automating compliance monitoring, risk detection, and reporting. These solutions adapt to evolving regulations, reduce manual effort, and improve accuracy—critical in a sector where compliance failures can have severe financial and reputational consequences.
Data Modernization: Modernizing data infrastructure is essential for real-time insights, predictive analytics, and regulatory reporting. Data leaders are investing in governance, advanced analytics, and machine learning infrastructure, enabling seamless integration of generative AI and unlocking new business opportunities.

Unlocking New Value Through AI-Driven Service Models

The shift to AI-led service models is transforming how card issuers operate and compete. By moving from labor-intensive, manual processes to services-as-software, issuers can:

Accelerate innovation and time-to-market for new card products and features.
Enhance customer and employee experiences through AI-powered chatbots, recommendation engines, and proactive service bots.
Drive operational agility and cost savings by automating routine tasks and enabling self-service capabilities.
Proactively manage risk and compliance with real-time monitoring and adaptive controls.

Overcoming Barriers: From Experimentation to Enterprise-Scale AI

Despite the promise of AI, many card issuers remain stuck in the experimentation phase. Key barriers include integration with legacy systems, data quality and governance challenges, regulatory and ethical concerns, and talent shortages. To move from pilots to production, card issuers must:

Treat tech debt like financial debt—track, prioritize, and eliminate it systematically.
Build around AI, not just bolt it onto existing systems.
Shift from labor-first outsourcing to outcome-based partnerships.
Redesign roles, processes, and culture for continuous AI-driven reinvention.

Actionable Strategies for Sustainable Modernization

Publicis Sapient’s SPEED model—Strategy, Product, Experience, Engineering, and Data & AI—provides a holistic framework for AI-driven modernization. Key strategies for card issuers include:

Modernize core systems: Migrate to cloud-native, API-first architectures that enable agility, scalability, and compliance.
Invest in data quality and governance: Unify data across silos, implement robust governance, and ensure data is accessible, accurate, and secure.
Automate compliance and risk management: Deploy AI-powered solutions to monitor, detect, and report on regulatory requirements in real time.
Foster a culture of innovation: Empower cross-functional teams, invest in upskilling, and embed continuous learning and experimentation.
Partner for success: Collaborate with technology leaders and proven AI experts to accelerate transformation and de-risk implementation.

Real-World Impact: Case Studies from Publicis Sapient

Publicis Sapient’s work with leading financial institutions demonstrates the tangible benefits of AI-driven modernization:

Deutsche Bank: Built an AI/ML catalog, modernized data infrastructure, and drove new business models—laying the foundation for rapid, sustainable AI value creation.
Operational Efficiency: For a multinational investment bank, AI-powered document imaging and automation streamlined email and unstructured data handling, saving tens of millions of dollars and driving significant process efficiencies.
Data Modernization: A UK-based retail bank accelerated time to insights for data scientists, enhancing productivity and enabling the bank to stay ahead in a competitive market.
Regulatory Compliance: AI integration into compliance workflows has automated regulatory processes, reduced manual effort, and improved accuracy—critical in a sector where compliance is non-negotiable.

The Path Forward: Building Future-Ready Card Issuers

The future belongs to card issuers that can break free from tech debt and harness AI as a driver of innovation, efficiency, and customer value. By addressing technology, data, process, skills, and cultural debts in tandem, issuers can move from incremental change to enterprise-scale transformation. With AI as the catalyst, card issuers can rewrite the rules of modernization, deliver hyper-personalized experiences, and lead the next wave of industry innovation.

Ready to smash through tech debt? Let’s talk about your modernization journey.